Biography
Dr. Li Bai is the Chair and Professor in the Electrical and Computer Engineering Department at Temple University. He has extensive research experience and expertise in distributed software computing, wireless sensor networks, system and software integration using commercial-off-the-shelf products and computer network security. He published over 60 peer-reviewed international journals and conference papers in the related areas. He has been involved in several sponsored research projects using portable devices with 802.11 wireless communication protocols. In addition, he was a core organizer in the 8th International Conference on Information Fusion held in Philadelphia in July 2005.
Labs: Computer Fusion Lab
Research Interests
- Distributed Software Computing
- Wireless Sensor Networks
- System and Software Integration Using Commercial-Off-the-Shelf Products and Computer Network Security.
Courses Taught
|
Number |
Name |
Level |
|---|---|---|
|
ECE 2612 |
Digital Circuit Design |
Undergraduate |
|
ECE 2613 |
Digital Circuit Design Laboratory |
Undergraduate |
|
ECE 3432 |
Robotic Control using Robotic Operating System (ROS) |
Undergraduate |
|
ECE 3432 |
Robotic Control using Raspberry Pi Microcontroller |
Undergraduate |
|
ECE 4532 |
Computer Network Communication |
Undergraduate |
Selected Publications
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Li, Y., Xie, D., Cember, A., Nanga, R.P.R., Yang, H., Kumar, D., Hariharan, H., Bai, L.i., Detre, J.A., Reddy, R., & Wang, Z.e. (2020). Accelerating GluCEST imaging using deep learning for B0 correction. Magn Reson Med, 84(4), pp. 1724-1733. United States. doi: 10.1002/mrm.28289
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Xie, D., Li, Y., Yang, H., Bai, L.i., Wang, T., Zhou, F., Zhang, L., & Wang, Z.e. (2020). Denoising arterial spin labeling perfusion MRI with deep machine learning. Magn Reson Imaging, 68, pp. 95-105. Netherlands. doi: 10.1016/j.mri.2020.01.005
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Xie, D., Li, Y., Yang, H.L., Song, D., Shang, Y., Ge, Q., Bai, L., & Wang, Z. (2019). BOLD fMRI-Based Brain Perfusion Prediction Using Deep Dilated Wide Activation Networks. Lecture Notes in Computer Science (including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11861 LNCS, pp. 373-381. doi: 10.1007/978-3-030-32692-0_43
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Kollmer, J.D., Biswas, S.K., Bai, L., Sarwat, A.I., & Saad, W. (2018). A hardware-in-the-loop experimental platform for power grid security. ASEE Annual Conference and Exposition, Conference Proceedings, 2018-June.